Granger Causality Test of Urban-rural Income Gap and Employment of Rural Labor Forces——A Case Study of Shouguang City

Taking Shouguang City in Shandong Province as an example, this article researches the mutual relationship between urban-rural income and employment of rural labor forces, and conducting cointegration test and Granger causality test on the variable sequences using statistical data. The results show that the average annual income of rural labor forces influences the income per capita of rural residents, and there is a Granger causality relationship between the income per capita of rural residents and urban employees' average wage. Engaging in production concerning agriculture, forestry, animal husbandry and fishery makes the total income per capita in rural areas of Shouguang City higher than the average wage of urban residents in Shouguang City, even in Weifang City. The comparative advantage in terms of income causes the city to loose attraction to rural residents in Shouguang City. The comparative advantage drives more rural labor forces in Shouguang City to engage in primary industry, thereby greatly reducing the pressure of employment and transfer of rural labor forces. Finally important following measures are put forward to promote employment and on-the-spot transfer of rural labor forces: vigorously propel agricultural industrialization; increase rural residents' income; improve the living conditions for rural residents.

Correlation analysis and causality test between Ludong-Huanghai block and South Japan

In this paper, we make a comparative analysis and correlation test for the seismic activities in the South Japan and the Ludong-Huanghai block （a secondary tectonic unit in the North China） and approach the relationship between the energy release processes of these two areas by using co-integration analysis and Granger causality test for the time series of random variables. The results show that the seismic activities in these two areas are correlative and synchronous to a certain extent, and their release series of cumulative strain energy are contemporaneously correlative. Both energy series are first-order difference stationary processes and there is secular and steady co-integration between them. We make a positive analysis on the first-order difference energy series through Granger causality test based on vector error correction （VEC） model and find there is unilateral Granger causality and prominent co-integration between the two energy release processes.

Rural Financial Development and Rural Economic Efficiency Improvement Based on Granger Causality Test

Based on the co-integration test theory,Financial Interrelation Ratio(FIR),level of financial efficiency(LFE),level of financial development(LFD) and other indices evaluating the rural financial development are selected by Granger Causality Test.The rural loan balance(RLB),rural deposit balance(RDB),total rural output(TRO),fixed assets investment(FAI),Financial Interrelation Ratio(FIR),economic efficiency(EE),level of financial efficiency(LFE),and level of financial development(LFD) in the years 1979-2007 are collected.Graphical method intuitively reflects the development trend and historical track of relevant indices;and Granger Causality Test verifies the relationship between rural financial development level and rural economic efficiency in the years 1979-2007.Result shows that rural financial development level has significant impact on rural economic growth,but rural economic growth has no significant impact on rural financial development;and rural financial development also has insignificant promotion impact on rural economic efficiency.Thus,conclusions are obtained.Although rural financial development has made certain contribution to the development of rural economy,this kind of contribution is only reflected in total quantity,but not efficiency.Therefore,government should further strengthen the promotion function of financial development for economic efficiency,and gradually establish a virtuous circle system for rural finance and economic development.

Properties of Time-Varying Causality Tests in the Presence of Multivariate Stochastic Volatility

This paper compares the statistical properties of time-varying causality tests when errors of variables have multivariate stochastic volatility (SV). The time-varying causal-ity tests in this paper are based on a logistic smooth transition autoregressive model. The compared time-varying causality tests include asymptotic tests, heteroskedasticity-robust tests, and tests using wild bootstrap. Our simulation results show that asymptotic tests and heteroskedasticity-robust counterparts have size distortions under multivariate SV, whereas tests using wild bootstrap have better size properties regardless of type of error. In particular, the time-varying causality test with first-order Taylor approximation using wild bootstrap has better statistical properties.

Research on the Relationship between Energy Minerals Exploitation and Economic Growth： Johansen Co-integration Analysis and Granger Causality Test

The purpose of this paper is to puts forward suggestions for the sustainable development of mineral resources by combining the benefit of economy from mineral resources with the introduction of concept of circular economic development.

Abnormal behavior detection by causality analysis and sparse reconstruction

A new approach for abnormal behavior detection was proposed using causality analysis and sparse reconstruction. To effectively represent multiple-object behavior, low level visual features and causality features were adopted. The low level visual features, which included trajectory shape descriptor, speeded up robust features and histograms of optical flow, were used to describe properties of individual behavior, and causality features obtained by causality analysis were introduced to depict the interaction information among a set of objects. In order to cope with feature noisy and uncertainty, a method for multiple-object anomaly detection was presented via a sparse reconstruction. The abnormality of the testing sample was decided by the sparse reconstruction cost from an atomically learned dictionary. Experiment results show the effectiveness of the proposed method in comparison with other state-of-the-art methods on the public databases for abnormal behavior detection.

Analysis of services trade and employment in China by co-integration and causality

This article describes a study by co-integration test and Granger causality test on the relationships between China's services trades and employment using the data of services trade from the WTO website and the employment data from China Statistic Yearbook for the years from 1982 to 2003. Co-integration test showed that 1% increase in export value and import value of services created respectively 0.205% and 0.068 7% more job opportunities in the service sector. Both export and import of services impacted positively on employment in service industry, and export did more than import. However, in the short run, the impacts of services export and import on employment in service industry were both very small, though positive; and the impacts of employment in service industry on both export and import of services were very big, but not stable. Granger causality test indicated that employment in service industry was a Granger cause of services export. The findings highlight the importance of facilitating services import and reducing import barriers, and suggest that the competitiveness of China's labor- intensive services trade can be exploited to boost services export and help employment in service sector, and that the structure of services trade should be optimized by shifting from labor-intensive to knowledge-and technology-intensive services thus to enhance China's competitiveness of services export.

Sample Size Calculation of Exact Tests for the Weak Causal Null Hypothesis in Randomized Trials with a Binary Outcome

The main purpose in many randomized trials is to make an inference about the average causal effect of a treatment. Therefore, on a binary outcome, the null hypothesis for the hypothesis test should be that the causal risks are equal in the two groups. This null hypothesis is referred to as the weak causal null hypothesis. Nevertheless, at present, hypothesis tests applied in actual randomized trials are not for this null hypothesis;Fisher’s exact test is a test for the sharp causal null hypothesis that the causal effect of treatment is the same for all subjects. In general, the rejection of the sharp causal null hypothesis does not mean that the weak causal null hypothesis is rejected. Recently, Chiba developed new exact tests for the weak causal null hypothesis: a conditional exact test, which requires that a marginal total is fixed, and an unconditional exact test, which does not require that a marginal total is fixed and depends rather on the ratio of random assignment. To apply these exact tests in actual randomized trials, it is inevitable that the sample size calculation must be performed during the study design. In this paper, we present a sample size calculation procedure for these exact tests. Given the sample size, the procedure can derive the exact test power, because it examines all the patterns that can be obtained as observed data under the alternative hypothesis without large sample theories and any assumptions.

复杂网络视角下京津冀晋鲁豫地区PM_(2.5)的相互作用特征及归因分析

为实现空气质量的有效监控,从复杂网络的视角研究PM_(2.5)的相互作用,在传统复杂网络的基础上,采用格兰杰因果检验方法确定京津冀晋鲁豫地区城市间PM_(2.5)作用关系,引入生物学中的营养一致性理论,探索PM_(2.5)网络层次特征,从经济社会因素和气象因素两种视角,对京津冀晋鲁豫地区PM_(2.5)复杂网络特征进行归因分析。结果发现:京津冀晋鲁豫地区PM_(2.5)具有显著的空间网络特征,区域间的相互作用关系和传输关系复杂,不同季节之间PM_(2.5)网络的稳定性不同;相比于高中介中心性节点,城市春秋两季网络的效率对度中心性高的节点更敏感,冬季则对二者的敏感程度相近;北京、郑州、济南、太原4个代表城市的PM_(2.5)浓度与经济社会因素之间有不同程度的相关关系,与气象因素之间则存在不同强度的长程正相关性特征。

事实因果关系的归责功能

“归因—归责”的阶层性判断框架对因果关系从事实到规范、从客观到主观的判断模式是法学界的共识,但对事实因果关系的判断是否只是单纯地适用条件公式值得研究。行为危险现实化说在特殊体质和介入型案件中采用比较事实原因力的方法降低规范判断承载的压力,把对危险实现的规范判断建立在事实因果关系判断的基础之上,在一定程度上恢复了事实因果关系的重要性。无论是从自然科学、社会科学还是从日常生活经验来看,事实因果关系都不是用形式化的“若无则不”公式判断的诸多等值条件关系。事实因果关系对法律因果关系具有判断和认知两种功能。危险创设阶段的事实因果关系主要是对心理类案件和不作为案件中的因果关系提供认知功能。危险实现阶段的事实因果关系可以为特殊体质案件和介入型案件提供基于事实原因力比较的判断功能;在因果关系存在科学不确定性的案件中,危险是如何具体实现的需要通过流行病学或其他学科的合法则的事实因果关系进行判断。并非所有案件都需要事实因果关系对归责的辅助性判断功能,在非疑难案件中,事实因果关系没有必要受到特别重视;在有些疑难案件中,疑难的确只存在于规范判断上,对于这些案件,事实因果关系只需要根据条件说即可验证。

基于时变传染网络和分位数Granger因果检验的系统性风险传染研究

基于18个经济体760家金融机构SRISK系统性风险数据,采用时变参数向量自回归模型和广义方差分解法测度全球系统性风险的时变传染网络,进而采用分位数Granger因果检验考察各经济体对中国高分位段系统性风险的影响。研究结果表明,结合SRISK数据和时变传染网络能有效识别重大风险事件的发生;发达和新兴经济体均会产生风险净输出效应,且会通过直接输出或香港地区间接输出风险至中国内地;在全样本与2008年金融危机、欧债危机、中美贸易战和新冠疫情重大风险事件期间,中国皆为风险净溢入国且新冠疫情期间溢入效应达历史最高;美英两国在重大风险事件期间均对中国高分位段系统性风险产生显著影响,新冠疫情期间中国高分位段系统性风险遭受外部冲击的形势最为严峻。

我国牛肉价格波动影响因素研究——基于VAR模型的实证分析

为保证牛肉价格合理稳定、推动牛肉市场持续健康发展,文章基于2011年12月—2022年12月中国畜牧业月度数据,以内部传导和外部冲击为视角,选取玉米价格、生产者预期、犊牛价格、国家政策构建VAR模型,实证检验我国牛肉价格波动影响因素及程度。结果显示,玉米价格、生产者预期、犊牛价格、国家政策均可对牛肉价格造成影响。其中,玉米价格可通过内部传导机制对我国牛肉价格波动产生显著影响,且稳定贡献率在8%左右;国家政策可通过外部冲击机制对我国牛肉价格波动形成显著影响,贡献率为15%;前期牛肉价格可显著影响后期牛肉市场价格。因此,文章提出降低肉牛产业饲料成本、加大肉牛产业政府财政支持力度、完善牛肉价格波动市场监管体系的建议,以期为稳定牛肉价格、促进畜牧产业可持续发展提供参考。

农业生产性服务业与新型农业经营主体耦合协调关系的实证研究--以吉林省为例

在乡村振兴和农村产业融合大背景下,正确认识和处理农业生产性服务业和新型农业经营主体之间的协调发展关系具有重要意义。为明确农业生产性服务业与新型农业经营主体两系统的耦合协调关系,基于吉林省2010-2022年农业生产性服务业与新型农业经营主体的时间序列数据,运用协整分析、Granger因果检验和耦合协调模型分析农业生产性服务业与新型农业经营主体间的互动关系和动态耦合发展趋势。结果表明:吉林省农业生产性服务业与新型农业经营主体发展水平持续攀升,分别由0.284 9提升至0.837 9、0.100 1提升至0.994 1;农业生产性服务业与新型农业经营主体两系统存在着显著正相关的长期均衡关系,且互为格兰杰原因,即农业生产性服务业是有效促进新型农业主体发展的重要原因,新型农业经营主体是推动推动农业生产性服务业提升的重要动力;2010-2022年,吉林省农业生产性服务业与新型农业经营主体之间的耦合协调关系上升趋势明显,先后经历拮抗阶段(0.410 9)、勉强协调(0.517 9~0.572 0)、初级协调(0.637 4)、中级协调(0.735 8~0.773 8)、高度协调(0.843 1~0.870 9~0.916 6~0.914 7~0.914 8~0.915 3~0.915 7)的变化过程,目前两系统处于关系稳定的高水平耦合阶段。未来应通过促进农业生产性服务业与新型农业经营主体协调发展推进现代农业进程。

通智测试——基于动态具身物理社会交互环境的通用人工智能测试

The release of the generative pre-trained transformer(GPT)series has brought artificial general intelligence(AGI)to the forefront of the artificial intelligence(AI)field once again.However,the questions of how to define and evaluate AGI remain unclear.This perspective article proposes that the evaluation of AGI should be rooted in dynamic embodied physical and social interactions(DEPSI).More specifically,we propose five critical characteristics to be considered as AGI benchmarks and suggest the Tong test as an AGI evaluation system.The Tong test describes a value-and ability-oriented testing system that delineates five levels of AGI milestones through a virtual environment with DEPSI,allowing for infinite task generation.We contrast the Tong test with classical AI testing systems in terms of various aspects and propose a systematic evaluation system to promote standardized,quantitative,and objective benchmarks and evaluation of AGI.

通货膨胀传导机制识别与通胀分型治理

采用时变Granger因果检验明确中国历次典型通胀时期下的通货膨胀传导机制与通胀成本负担状况,并基于反事实模拟给出结构性通货膨胀的治理方略。研究结果显示:(1)2012年前中国的通货膨胀基本都是全局性通胀,而在2012年后,通货膨胀则具有典型的结构性特征;(2)治理全局性通胀只需盯住通胀源头和成本终端,而治理结构性通胀则应关注疏通通胀传导链条;(3)当下的通货紧缩是一轮由最终消费端发起的全局性通缩,但由于此轮通缩中只存在价格逆向传导链条,导致其仍有演化为结构性通缩的可能;(4)面对结构性通货紧缩,中央银行应采取适度盯住生产端价格指数的方式予以治理,这不仅有利于事前化解可能出现的产业链断裂风险,而且也能为后疫情时期的经济复苏营造良好的宏观环境和增长空间。

基于时空认知膨胀卷积网络与多源影响因素的PM_(2.5)细粒度预测模型

为实现精确化、细粒度的PM_(2.5)浓度预测,提出了基于时空认知膨胀卷积网络(spatial-temporal cognitive dilated convolution network,ST-C-DCN)的PM_(2.5)浓度预测模型ST-C-DCN。该模型将时空因素、气象因素运用于PM_(2.5)浓度预测,基于因果卷积网络提取时空特征,并采用时空注意力机制优化了时空特征的提取。基于海口市空气污染数据的实验测试表明:对于单个监测站,基线模型相比,ST-C-DCN的均方根误差(root mean square error,RMSE)平均下降24.7%,平均绝对误差(mean absolute error,MAE)平均下降9.93%,拟合优度(R-squared,R^(2))平均上升3.35%。对于全部监测站点的预测,ST-C-DCN在win-tie-loss(包括MSE、RMSE、MAE、R^(2))实验中,均获得了最多的获胜次数,分别为68,68、63和64。通过不同数据抽样条件下的Friedman检验,证明了ST-C-DCN对比基准有显著的性能提升。ST-C-DCN为细粒度PM_(2.5)预测提供了一个具有潜力的方向。

基于自适应阈值学习的时序因果推断方法

时序数据存在近因性特点,即变量值普遍依赖近期的历史信息,而现有时序因果推断方法没有充分考虑时序数据的这种特性,在通过假设检验推断不同延迟的因果关系时使用统一的阈值,难以有效推断较弱的因果关系。针对上述问题,提出基于自适应阈值学习的时序因果推断方法:首先提取数据特性,其次根据不同延迟下数据呈现的性质,自动地学习假设检验过程中使用的阈值组合,最后将该阈值组合用于PC(Peter-Clark)算法、PCMCI(Peter-Clark and Momentary Conditional Independence)算法和VAR-LINGAM(Vector AutoRegressive LINear non-Gaussian Acyclic Model)算法的假设检验过程,以得到更准确的因果关系结构。在仿真数据集上的实验结果表明,采用所提方法的自适应PC算法、自适应PCMCI算法和自适应VAR-LINGAM算法的F1值都有所提高。

危机情境下网络反向议程设置的探测及预测

[目的/意义]反向议程设置探测方法能够动态捕捉危机情境下局部而短暂的反向议程设置效应,反向议程设置的预测模型有助于理解危机信息从公众议程进入媒体议程的过程,能够有效追踪舆情动态并辅助危机报道的选题。[方法/过程]采用滑动时间窗口和格兰杰因果检验,动态探测危机情境下的反向议程设置效应;基于新闻价值和资源动员理论,从内容价值、媒体差异、话语风格、动员举措和成员网络5个方面提出反向议程设置的特征体系,采用逻辑回归、朴素贝叶斯、支持向量机、CART决策树和XGBoost训练反向议程设置预测模型,使用XGBoost解释特征重要性排序,利用SHAP解释特征影响。[结果/结论]公众议程与媒体议程的领先关系随着危机议题的发展动态变化,媒体议程影响公众议程的速度高于公众议程影响媒体议程的速度。危机情境下基于XGBoost的反向议程设置预测模型效果最好,准确率达到91.04%,F1值达到90.80%,AUC值达到96.58%;内容价值、媒体差异特征对预测结果重要性最高。

欧盟碳交易市场的影响因素研究

为探究欧盟碳交易市场的影响因素,本文选取2013年1月1日至2022年8月31日的欧盟碳排放配额(EUA)期货的日收益率为研究对象,通过协整检验及格兰杰因果检验对EUA期货及市场影响因素进行实证分析。实证结果显示:EUA期货价格与各影响因素之间存在长期均衡关系,煤炭价格与石油价格负向影响碳排放配额定价,天然气价格与股票指数正向影响碳排放配额定价。煤炭价格与EUA价格存在双向因果关系,石油价格与EUA价格存在单向因果关系。本文通过研究较为成熟的欧盟碳排放交易市场从优化能源结构、加快产业升级、稳定宏观经济和完善碳排放交易体系方面为中国新兴碳排放交易市场的发展提供建议。

金融行业发展对经济增长的影响——基于VAR模型的实证分析

基于金融发展服务于经济增长视角,构建两个VAR模型,选择1978年到2022年的GDP、M2、社会融资规模、股票成交额、债券成交额、期货成交额以及保险公司保费的时间面板数据分别实证分析了金融及其行业发展与经济增长的影响。主要分析了各指标与经济增长指标的Granger因果关系、Johansen协整关系以及脉冲响应函数等情况。通过分析发现,金融发展是经济增长的Granger原因,金融各行业发展均不是经济增长的Granger原因;经济发展受自身影响同时,金融及其行业发展变化对其也产生不小影响,债券成交额、M2、保险公司保费等影响较大。基于分析结论,提出了监管货币流通、畅通融通渠道、加强股票市场调整和监管、扩大保险业务范围、严厉整顿债券和期货市场等5条建议。